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Modeling truck scheduling problem at a cross-dock facility through a bi-objective bi-level optimization approach

Author

Listed:
  • Fateme Heidari

    (Industrial Engineering of Tarbiat Modares University)

  • Seyed Hessameddin Zegordi

    (Tarbiat Modares University)

  • Reza Tavakkoli-Moghaddam

    (University of Tehran)

Abstract

Uncertainty and non-deterministic nature of the real world makes planning and scheduling in cross-docks a very complicated task for decision makers. These constant changes that happen all the time, often, lead to an increase in costs and/or a decrease in efficiency. Most of the uncertainty in cross-docks is caused by un-known truck arrival times. In this study we address the problem of scheduling incoming and outgoing trucks at a cross-dock facility, when vehicle arrival times are unknown, through a cost-stable scheduling strategy. Two meta-heuristics, MODE and NSGA-II, are used for solving the designed sample problems and are compared with a random search based genetic algorithm existing in the literature. Finally, performance of each algorithm is measured and analyzed using four metrics: quality, spacing, diversification and mean ideal distance. The results indicate that the proposed model MODE algorithm performs better in comparison with the other two methods.

Suggested Citation

  • Fateme Heidari & Seyed Hessameddin Zegordi & Reza Tavakkoli-Moghaddam, 2018. "Modeling truck scheduling problem at a cross-dock facility through a bi-objective bi-level optimization approach," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1155-1170, June.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:5:d:10.1007_s10845-015-1160-3
    DOI: 10.1007/s10845-015-1160-3
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    References listed on IDEAS

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    1. Chen, Feng & Lee, Chung-Yee, 2009. "Minimizing the makespan in a two-machine cross-docking flow shop problem," European Journal of Operational Research, Elsevier, vol. 193(1), pages 59-72, February.
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    4. Konur, Dinçer & Golias, Mihalis M., 2013. "Cost-stable truck scheduling at a cross-dock facility with unknown truck arrivals: A meta-heuristic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 71-91.
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    Cited by:

    1. Rijal, Arpan & Bijvank, Marco & de Koster, René, 2019. "Integrated scheduling and assignment of trucks at unit-load cross-dock terminals with mixed service mode dock doors," European Journal of Operational Research, Elsevier, vol. 278(3), pages 752-771.
    2. Abdul Salam Khan & Qazi Salman Khalid & Khawar Naeem & Rafiq Ahmad & Razaullah Khan & Waqas Saleem & Catalin Iulian Pruncu, 2021. "Application of Exact and Multi-Heuristic Approaches to a Sustainable Closed Loop Supply Chain Network Design," Sustainability, MDPI, vol. 13(5), pages 1-25, February.
    3. Dulebenets, Maxim A., 2019. "A Delayed Start Parallel Evolutionary Algorithm for just-in-time truck scheduling at a cross-docking facility," International Journal of Production Economics, Elsevier, vol. 212(C), pages 236-258.
    4. Xi, Xiang & Changchun, Liu & Yuan, Wang & Loo Hay, Lee, 2020. "Two-stage conflict robust optimization models for cross-dock truck scheduling problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    5. Tarik Chargui & Abdelghani Bekrar & Mohamed Reghioui & Damien Trentesaux, 2019. "Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption," Sustainability, MDPI, vol. 11(11), pages 1-23, June.
    6. Maxim A. Dulebenets, 2018. "A Diploid Evolutionary Algorithm for Sustainable Truck Scheduling at a Cross-Docking Facility," Sustainability, MDPI, vol. 10(5), pages 1-23, April.
    7. Ieva Meidute-Kavaliauskiene & Nihal Sütütemiz & Figen Yıldırım & Shahryar Ghorbani & Renata Činčikaitė, 2022. "Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption," Energies, MDPI, vol. 15(4), pages 1-24, February.
    8. Gaudioso, Manlio & Monaco, Maria Flavia & Sammarra, Marcello, 2021. "A Lagrangian heuristics for the truck scheduling problem in multi-door, multi-product Cross-Docking with constant processing time," Omega, Elsevier, vol. 101(C).

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